diff --git a/src/scgenerator/spectra.py b/src/scgenerator/spectra.py
index 0976b8a..937e38a 100644
--- a/src/scgenerator/spectra.py
+++ b/src/scgenerator/spectra.py
@@ -1,9 +1,8 @@
 from __future__ import annotations
 
 import os
-import warnings
 from pathlib import Path
-from typing import Callable
+from typing import Callable, Generic, TypeVar, overload
 
 import numpy as np
 
@@ -15,10 +14,12 @@ from scgenerator.io import (
     ZipFileIOHandler,
     unique_name,
 )
+from scgenerator.logger import get_logger
 from scgenerator.parameter import Parameters
 from scgenerator.physics import pulse, units
 
 PARAMS_FN = "params.json"
+ParamsOrNone = TypeVar("ParamsOrNone", Parameters, None)
 
 
 class Spectrum(np.ndarray):
@@ -138,27 +139,28 @@ class Spectrum(np.ndarray):
         return pulse.measure_field(self.t, self.time_amp)
 
 
-class Propagation:
+class Propagation(Generic[ParamsOrNone]):
     io: PropagationIOHandler
-    parameters: Parameters
+    parameters: ParamsOrNone
     _current_index: int
 
     def __init__(
-        self,
+        self: Propagation[ParamsOrNone],
         io_handler: PropagationIOHandler,
-        params: Parameters,
+        params: ParamsOrNone,
     ):
         """
         A propagation is the object that manages IO for one single propagation.
-        It is recommended to use the "memory_propagation" and "zip_propagation" convenience
-        factories instead of creating this object directly.
+        It is recommended to use the "propagation" convenience factories instead of creating this
+        object directly.
 
         Parameters
         ----------
         io : PropagationIOHandler
             object that implements the PropagationIOHandler Protocol.
-        params : Parameters
-            simulations parameters. Those will be saved via the
+        params : Parameters | None
+            simulations parameters. Those will be passed on to spectra when loaded.
+            if None, loading spectra will result in normal numpy arrays rather than `Spectrum` obj.
         """
         self.io = io_handler
         self._current_index = len(self.io)
@@ -167,26 +169,47 @@ class Propagation:
     def __len__(self) -> int:
         return self._current_index
 
-    def __getitem__(self, key: int | slice) -> Spectrum:
+    @overload
+    def __getitem__(self: Propagation[Parameters], key: int | slice) -> Spectrum:
+        ...
+
+    @overload
+    def __getitem__(self: Propagation[None], key: int | slice) -> np.ndarray:
+        ...
+
+    def __getitem__(self, key: int | slice) -> Spectrum | np.ndarray:
         if isinstance(key, slice):
             return self._load_slice(key)
         if isinstance(key, (float, np.floating)):
+            if self.parameters is None:
+                raise ValueError(f"cannot accept float key {key} when parameters is not set")
             key = math.argclosest(self.parameters.compute("z_targets"), key)
         elif key < 0:
             key = len(self) + key
         array = self.io.load_spectrum(key)
-        return Spectrum(array, self.parameters)
+        if self.parameters is not None:
+            return Spectrum(array, self.parameters)
+        else:
+            return array
 
     def __setitem__(self, key: int, value: np.ndarray):
         if not isinstance(key, int):
             raise TypeError(f"Cannot save a spectrum at index {key!r} of type {type(key)!r}")
         self.io.save_spectrum(key, np.asarray(value))
 
+    @overload
+    def _load_slice(self: Propagation[Parameters], key: slice) -> Spectrum:
+        ...
+
+    @overload
+    def _load_slice(self: Propagation[None], key: slice) -> np.ndarray:
+        ...
+
     def _load_slice(self, key: slice) -> Spectrum:
         _iter = range(len(self))[key]
-        out = Spectrum(
-            np.zeros((len(_iter), self.parameters.t_num), dtype=complex), self.parameters
-        )
+        out = np.zeros((len(_iter), self.parameters.t_num), dtype=complex)
+        if self.parameters is not None:
+            out = Spectrum(out, self.parameters)
         for i in _iter:
             out[i] = self.io.load_spectrum(i)
         return out
@@ -204,6 +227,7 @@ def propagation(
     params: Parameters | None = None,
     bundle_data: bool = False,
     overwrite: bool = False,
+    load_parameters: bool = True,
 ) -> Propagation:
     file = None
     if isinstance(file_or_params, Parameters):
@@ -213,7 +237,7 @@ def propagation(
 
     if file is not None and file.exists() and params is None:
         io = ZipFileIOHandler(file)
-        return _open_existing_propagation(io)
+        return _open_existing_propagation(io, load_parameters=load_parameters)
 
     if params is None:
         raise ValueError("Parameters must be specified to create new simulation")
@@ -235,7 +259,11 @@ def propagation(
         raise e
 
 
-def _open_existing_propagation(io: PropagationIOHandler) -> Propagation:
+def _open_existing_propagation(
+    io: PropagationIOHandler, load_parameters: bool = True
+) -> Propagation:
+    if not load_parameters:
+        return Propagation(io, None)
     params = Parameters.from_json(io.load_data(PARAMS_FN).decode())
     params.compile_in_place(exhaustive=True, strict=False)
     for k, v in params.items():